Package elki.distance.minkowski

Class SparseLPNormDistance

java.lang.Object

elki.distance.minkowski.SparseLPNormDistance

All Implemented Interfaces:

Distance<SparseNumberVector>, Norm<SparseNumberVector>, PrimitiveDistance<SparseNumberVector>

Direct Known Subclasses:

SparseEuclideanDistance, SparseManhattanDistance, SparseMaximumDistance

public class SparseLPNormDistance
extends java.lang.Object
implements PrimitiveDistance<SparseNumberVector>, Norm<SparseNumberVector>

L_p-Norm, optimized for SparseNumberVectors.

The L_p distance is defined as: \[ L_p(\vec{x},\vec{y}) := \left(\sum\nolimits_i (x_i-y_i)\right)^{1/p} \]

Since:

0.5.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	SparseLPNormDistance.Par	Parameterizer

Field Summary

Fields

Modifier and Type	Field	Description
private double	invp	Parameter and its inverse.
private double	p	Parameter and its inverse.

Constructor Summary

Constructors

Constructor	Description
SparseLPNormDistance(double p)	Constructor.

Method Summary

Modifier and Type	Method	Description
double	distance(SparseNumberVector v1, SparseNumberVector v2)	Computes the distance between two given DatabaseObjects according to this distance function.
SimpleTypeInformation<? super SparseNumberVector>	getInputTypeRestriction()	Get the input data type of the function.
boolean	isMetric()	Is this distance function metric (satisfy the triangle inequality)
double	norm(SparseNumberVector v1)	Compute the norm of object obj.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface elki.distance.Distance

isSquared, isSymmetric

Methods inherited from interface elki.distance.PrimitiveDistance

instantiate

Field Detail

p

private double p

Parameter and its inverse.

invp

private double invp

Parameter and its inverse.

Constructor Detail

SparseLPNormDistance

public SparseLPNormDistance(double p)

Constructor.

Method Detail

distance

public double distance(SparseNumberVector v1,
                       SparseNumberVector v2)

Description copied from interface: PrimitiveDistance

Computes the distance between two given DatabaseObjects according to this distance function.

Specified by:

distance in interface PrimitiveDistance<SparseNumberVector>

Parameters:

v1 - first DatabaseObject

v2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

norm

public double norm(SparseNumberVector v1)

Description copied from interface: Norm

Compute the norm of object obj.

Specified by:

norm in interface Norm<SparseNumberVector>

Parameters:

v1 - Object

Returns:

Norm

getInputTypeRestriction

public SimpleTypeInformation<? super SparseNumberVector> getInputTypeRestriction()

Description copied from interface: Distance

Get the input data type of the function.

Specified by:

getInputTypeRestriction in interface Distance<SparseNumberVector>

Specified by:

getInputTypeRestriction in interface PrimitiveDistance<SparseNumberVector>

Returns:

Type restriction

isMetric

public boolean isMetric()

Description copied from interface: Distance

Is this distance function metric (satisfy the triangle inequality)

Specified by:

isMetric in interface Distance<SparseNumberVector>

Returns:

true when metric.